Search

Purpose: Sustaining healthcare operations without adequate energy capacity creates significant challenges, especially during periods of constrained energy supply. This research develops a clinical and non-clinical activity-based hospital energy model for electrical load prioritization during periods of constrained energy supply. Design/methodology/approach: Discrete event modelling is adopted for development of the hospital energy model (HEM). The building block of the HEM is business process mapping of a hospitals clinical and non-clinical activities. The model prioritizes the electrical load demand as Priority 1, 2 and 3; Priority 1 activities are essential to the survival of patients, Priority 2 activities are critical activities that are required after one to four hours, and Priority 3 activities can run for several hours without electricity. Findings: The model was applied to small, medium, and large hospitals. The results demonstrate that Priority 2 activities have the highest energy demand, followed by Priority 1 and Priority 3 activities, respectively for all hospital sizes. For the medium and large hospitals, the top three contributors to energy demand are lighting, HVAC, and patient services. For the small hospital, it is patient services, lighting, and HVAC. Research limitations/implications: The model is specific to hospitals but can be modified for other healthcare facilities. Practical implications: The resolution of the electrical energy demand down to the business activity level enables hospitals to evaluate current practices for optimization. It facilitates multiple energy supply scenarios, enabling hospital management to conduct feasibility studies based on available power supply options Social implications: Improved planning of capital expenditure and operational budgets. Improved operations during periods of constrained energy supply, which reduces the risk to hospitals and ensures consistent quality of service. Originality/value: Current hospital energy models are limited, especially for operations management under constrained energy supply. A simple to use model is proposed to assist in planning of activities based on available supply

Purpose: Implementing process management methodology through Lean Management and Design Thinking provides a new way to manage surgical blocks, maximize efficiency and adapt to the high variability of demand. This article presents our experience of implementing a set of improvement actions within the surgical process in the context of Lean Healthcare Processes. The project involved a total of 900 healthcare professionals over a 3-year period (2017-2019) and has impacted over 38,000 surgical patients each year at the Vall d’Hebron University Hospital in Barcelona, Spain. The purpose of this article is to present a set of improvement projects within the surgical process and show the indicators that monitor its evolution. These projects have been implemented successfully in a hospital with high surgical complexity and indicate how health care professionals and process engineers can work together as a team to improve healthcare resources. Design/methodology/approach: To evaluate the effectiveness of the actions presented, we propose a series of standardized indicators showing how our findings increase the efficiency of the surgical process. We also indicate Lean projects that can reduce patient waiting times and increase capacity. Below is a management model for the surgical process that considers industrial production criteria such as resource planning, optimizing the use of operating rooms and professionals’ time and generating the best surgery combinations. Findings: Projects that have increased efficiency in the surgical block the most have been standardized and converted into a model of action. This is designed to adapt to any level of complexity within the hospital process. The set of improvement projects has been divided into 6 stages: Programming, Material logistics process, pre-surgical stage, intra-surgical stage, post-surgical stage and transversal projects; each affecting a different area of the general hospital (not only the surgical unit). Furthermore, a visual flow chart was designed using the results of the project. Findings from the study have led to a 15% increase in surgical capacity without the need for new resources. The average hospital stay also dropped from 7.2 days to 4.1 days. The flow vision in the care process improves the experience of both patients and health care professionals, who see their participation as part of the whole health care process. Research limitations/implications: the projects were mainly developed at the Vall d’Hebron University Hospital. Although several of these projects have been carried out in other hospitals in Spain by the same team of process engineers, results may be biased when the team provides support within its own process department, compared to when it supports the local team in another hospital temporarily. Another important limitation is that it takes several months to implement and consolidate the improvement projects and demonstrate improved indicators in a sustainable way over time. This matrix of projects is more than a specific action, a cultural change with the entire surgical department. Originality/value: This study sets out a proposed practical example of applying surgery management tools in the surgical process. Our proposal can offer hospital managers and surgical coordinators an orderly, streamlined project guide for overall surgical performance indicators. The main results from developing the model include the degree of satisfaction shown by healthcare professionals and the determined commitment from the center’s management team to promote process management using Lean methodology. This commitment continued despite the challenges of shifting the organizational structure towards process management, which is a complex task requiring a period of adaptation and learning. Healthcare management has always prioritized increasing surgical patient safety and satisfaction. Patient flows are increased and resources used more efficiency by shifting the focus to the patient and the processes gone through during their hospital stay. This improvement project provides us with the best example of Lean methodology implementation if reinvested in bettering healthcare. This in turn increases the value perceived by patients, which is the ultimate purpose of the process

BackgroundHospital Sant Joan de Déu (Barcelona) initiated a pediatric acute home-hospitalization program. Due to high patient turnover and the health staff's lack of planning training, daily scheduling was a time-consuming task. Home-hospitalization planning is a vehicle routing problem that can be solved with a technological solution. It was therefore decided to evaluate the efficacy and necessity of the SmartMonkey.io planner.ObjectivesTo compare traditional manual route planning with a route optimizer, and to evaluate the technical feasibility of the implementation of a route planner into a homecare program.MethodsEight participants (experienced homecare staff and inexperienced hospital staff) were included. Personal interviews were performed to assess their eagerness to try a technological solution to the planning problem. Objective benefits including reduced travel time (time planning, distance traveled, and time traveled) were evaluated. Paired t-test, t-test, and Pearson's correlation were used to compare manual and route planner scheduling. Participants then answered a questionnaire to assess planning difficulty and the acceptance of the route planner.ResultsHomecare staff were initially reluctant to use the technology. Significant differences (P < 0.0001) in three variables were found between manual planning and the route planner. A moderate correlation between time planning and plan difficulty (r = 0.59, P < 0.0001) was found with manual planning but not with the route planner. All route planner schedules saved time and distance. No significant differences were found between expertise and planning method. It was noted that it was easy to create plans with the route planner, while difficulty with manual planning increased as more locations were added. All participants evaluated the route planning tool favorably.ConclusionsRoute-planning technology saved planning time and generated better plans than manual planning. The route planner's learning curve was fast and results were obtained in the same amount of time regardless of difficulty and expertise. SmartMonkey.io also has the potential to reduce internal and environmental costs and increase staff productivity.

Purpose: Providing timely access is an important measure of patient satisfaction in specialty care clinics such as cancer centers. Excessive patient wait time to see an oncologist is very critical for cancer patients as they often benefit from starting the treatment process as soon as possible. This paper addresses capacity planning for both new and returning patients in cancer clinics. This research is motivated by a cancer center in Texas that seeks to improve its clinical performance to decrease new patient wait time to see an oncologist.Design/methodology/approach: A simulation model is proposed to assess new patient access to oncologists when employing several tactical and operational policies such as resource flexibility, specialization flexibility, and reserving slots for new patients. The model utilizes two years of data collected from a cancer center in Texas.Findings: The results suggest the best combination of operating policies in order to allocate patient demand to providers. This study also determines the required capacity level to provide timely access for new patients.Originality/value: Although the literature in outpatient scheduling and capacity planning is rich, new patient access in oncology clinics has received limited attention. The few existing studies do not consider patient no-shows and cancellations, and to the best of our knowledge, no study addresses individual oncologist clinic flexibility and the idea of reserving slots for new patients.